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Improving Multiclass Pattern Recognition by the Combination of Two Strategies
June 2006 (vol. 28 no. 6)
pp. 1001-1006
We present a new method of multiclass classification based on the combination of one-vs-all method and a modification of one-vs-one method. This combination of one-vs-all and one-vs-one methods proposed enforces the strength of both methods. A study of the behavior of the two methods identifies some of the sources of their failure. The performance of a classifier can be improved if the two methods are combined in one, in such a way that the main sources of their failure are partially avoided.

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Index Terms:
Multiclass, classification, one-vs-one, one-vs-all, neural networks, support vector machines.
Citation:
Nicol? Garc?a-Pedrajas, Domingo Ortiz-Boyer, "Improving Multiclass Pattern Recognition by the Combination of Two Strategies," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 6, pp. 1001-1006, June 2006, doi:10.1109/TPAMI.2006.123
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